Machine Learning (ML) Data: Best Machine Learning Datasets & Databases
What is Machine Learning (ML) Data?
Machine Learning (ML) data is the information used to train and develop machine learning models. It consists of examples or instances, often represented as numerical values or features. On this page, you’ll find the best data sources for various types of machine learning data.
Best Machine Learning (ML) Datasets & APIs
Factori AI & ML Training Data | Consumer Data | USA | Machine Learning Data
by
Factori
Available for 1 countries
300 + Million Profiles
1 years of historical data
97% fill rate
Starts at
$360,000 / year
Free sample preview
AI & ML Training Data | Artificial Intelligence (AI) | Machine Learning (ML) Datasets | Deep Learning Datasets | Easy to Integrate | Free Sample
by
APISCRAPY
Available for 61 countries
50M Records
30 days of historical data
100% Data Coverage
Starts at
$25 / month
Grepsr | AI & ML Training Data | Machine Learning Data | Tailored Web Data
by
Grepsr
Available for 249 countries
Pricing available upon request
Nexdata |Gesture Recognition Data |10,000Â ID | Computer Vision Data| AI Training Data | Machine Learning (ML) Data
by
Nexdata
Available for 124 countries
10K id
5 years of historical data
97% Accuracy
Starts at
$5,000 / purchase
Free sample preview
FileMarket | 20,000 photos | AI Training Data | Large Language Model (LLM) Data | Machine Learning (ML) Data | Deep Learning (DL) Data |
by
FileMarket
Available for 249 countries
20K photos
95% accuracy
Pricing available upon request
Free sample preview
Acoustic Guitar Dataset for AI-Generated Music (Machine Learning (ML) Data)
by
Rightsify
Available for 249 countries
100K Tracks
Starts at
$10,000 / year
Free sample preview
Bright Data | Data for AI & ML Training | Web Data Extraction Services for AI and Machine Learning (ML) Applications | GDPR Compliant
by
Bright Data
Available for 245 countries
97% Success rate in real-time
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
Soundsnap | 50K Music tracks | Machine Learning (ML) Music data | Stems | Professionally mixed | Cleared for ML/ AI
by
Soundsnap
Available for 249 countries
50K music tracks
10 years of historical data
80% instrumental
Starts at
$500,000 / purchase
Free sample preview
Factori AI & ML Training Data | Point of Interest Data (POI) | Global | Machine Learning Data
by
Factori
Available for 248 countries
420M MAU
1 years of historical data
95% Match rate
Starts at
$25,000$22,500 / purchase
Free sample preview
10% Datarade discount
Nexdata | Re-ID Data | 60,000Â ID |Computer Vision Data |Image/Video Machine Learning (ML) Data| Identity Data
by
Nexdata
Available for 133 countries
60K id
10 years of historical data
97% Accuracy
Starts at
$5,000 / purchase
Free sample preview
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Machine Learning (ML) Data Use Cases
Examples of Machine Learning (ML) Data
Examples of ML data include text documents, images, audio recordings, sensor data, and customer behavior data. Machine learning data is part of AI training data and is used to make predictions, classify data, recognize patterns, and automate decision-making processes.
What are the Different Types of Machine Learning (ML) Training Data?
- Textual Data: Used in natural language processing (NLP) tasks like sentiment analysis, language translation, and chatbot development.
- Annotated Imagery Data: Essential for computer vision applications such as image recognition, object detection, and facial recognition.
- Synthetic Data: Generated data that mimics real-world data, useful for training models when real data is scarce or privacy concerns are paramount.
- Audio Data: Used in speech recognition, voice assistants, and audio classification tasks.
How is the Machine Learning (ML) Training Data Collected?
Datasets for Machine Learning can be sourced from:
- Commercial Data Providers: Companies that sell specialized datasets. Datarade offers high-quality, curated datasets from reputable providers, ensuring data quality for specific ML applications.
- Public Databases: Open-access repositories and government portals offer datasets that are suitable for some use cases, such as study or university projects.
- Generated Data: Synthetic data can be created to simulate real-world scenarios.
- Internal Data: Data collected and maintained by organizations from their own operations, customers, and processes.
How to Train an Machine Learning Model with Data?
Training a Machine Learning model with data involves 7 steps:
- Data Collection: Gather relevant data from various sources.
- Data Preprocessing: Clean and prepare the data, handling missing values and normalizing features.
- Feature Selection: Identify the most important features that influence the target variable.
- Model Selection: Choose an appropriate algorithm for the task.
- Training: Use the training data to teach the model to recognize patterns.
- Evaluation: Assess the performance using test data.
- Tuning: Adjust model parameters to improve accuracy.